Mining evolutionary topic patterns in community question answering systems

Zhongfeng Zhang, Qiudan Li, Dajun Zeng

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Community Question Answering (CQA) is becoming a popular Web 2.0 application. By analyzing evolutionary topic patterns from CQA applications, one can gain insights into user interests and user responses to external events. This paper proposes a novel evolutionary topic pattern mining approach. This approach consists of three components: 1) extraction of the topics being discussed through a temporal analysis; 2) discovery of topic evolutions and construction of evolutionary graphs of extracted topics; and 3) life cycle modeling of the extracted topics. We show empirically the effectiveness of our approach using two real-world data sets.

Original languageEnglish (US)
Article number5928431
Pages (from-to)828-833
Number of pages6
JournalIEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans
Volume41
Issue number5
DOIs
StatePublished - Sep 2011

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Life cycle

Keywords

  • Community Question Answering (CQA)
  • evolutionary topic patterns
  • life cycle

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Human-Computer Interaction
  • Information Systems
  • Software

Cite this

Mining evolutionary topic patterns in community question answering systems. / Zhang, Zhongfeng; Li, Qiudan; Zeng, Dajun.

In: IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans, Vol. 41, No. 5, 5928431, 09.2011, p. 828-833.

Research output: Contribution to journalArticle

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